docstr: Plot of the treated vs untreated.
docstr_tok: ["Plot","of","the","treated","vs","untreated","."]
code: def discrete_dist_plot(
      labels,
      not_treated_counts,
      treated_counts,
      ax,
      title,
      var_name,
      font_size,
      width=0.35,
  ):
      """
      Plot of the treated vs untreated.
      """
  
      ax.bar(
          labels - width / 2,
          not_treated_counts,
          width,
          label="Untreated",
      )
      ax.bar(labels + width / 2, treated_counts, width, label="Treated")
      ax.set_xlabel(var_name)
      ax.set_ylabel("Count")
      ax.set_title(title, fontsize=font_size)
      ax.set_xticks(labels)
      ax.set_xticklabels(labels)
      ax.legend()
  
file_path: dowhy/dowhy/interpreters/confounder_distribution_interpreter.py
imports: import numpy
  import pandas
  from dowhy.causal_estimator import CausalEstimate
  from dowhy.causal_estimators.propensity_score_weighting_estimator import PropensityScoreWeightingEstimator
  from dowhy.interpreters.visual_interpreter import VisualInterpreter
label_desc: Use image node_id 2 for calling the ConfounderDistributionInterpreter obj's underlying member method code with example usage: obj.discrete_dist_plot(labels, not_treated_counts, treated_counts, ax, title, var_name, font_size, width) without return types